@inproceedings{6f6153da8d574418ab6f43f26cfaee8d,
title = "Botnet Attacks Detection using Image Processing Approach: Sequential Neural Network and Feature Selection",
abstract = "Botnets are networks of compromised computers that are controlled by an attacker for malicious purposes such as spamming attacks, DDoS, or data theft. Botnet attacks detection is a challenging task due to their distributed and covert nature. Botnet attacks are a major security concern for organizations and individuals alike. In this paper we proposed a botnet attacks detection using image processing approach. We propose an AI model architecture using Sequential Neural Network and feature selection. There are two methods for converting raw data into image data. First method using predefined categorize for choosing features. The second method uses Pearson correlation value between features in dataset and the label. Predefined categorized features have successfully increased the performance of proposed AI model for botnet attacks detection as well as Pearson correlation value.",
keywords = "Botnets, Computer Vision, Feature Selection, Pearson Correlation, Sequential Neural Network",
author = "Putra, {Taufiq Odhi Dwi} and Tohari Ahmad",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023 ; Conference date: 06-07-2023 Through 08-07-2023",
year = "2023",
doi = "10.1109/ICCCNT56998.2023.10307148",
language = "English",
series = "2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023",
address = "United States",
}